Package 'CohortConstructor' reference manual

Title:	Build and Manipulate Study Cohorts Using a Common Data Model
Description:	Create and manipulate study cohorts in data mapped to the Observational Medical Outcomes Partnership Common Data Model.
Authors:	Edward Burn [aut, cre] , Marti Catala [aut] , Nuria Mercade-Besora [aut] , Marta Alcalde-Herraiz [aut] , Mike Du [aut] , Yuchen Guo [aut] , Xihang Chen [aut] , Kim Lopez-Guell [aut] , Elin Rowlands [aut]
Maintainer:	Edward Burn <[email protected]>
License:	Apache License (>= 2)
Version:	0.3.2
Built:	2024-11-12 04:32:32 UTC
Source:	CRAN

Add an index to a cohort table

Description

Adds an index on subject_id and cohort_start_date to a cohort table. Note, currently only indexes will be added if the table is in a postgres database.

Usage

addCohortTableIndex(cohort)
addCohortTableIndex(cohort)

Arguments

cohort

A cohort table in a cdm reference.

Value

The cohort table

Benchmarking results

Description

Benchmarking results

Usage

benchmarkData
benchmarkData

Format

A list of results from benchmarking

Collapse cohort entries using a certain gap to concatenate records.

Description

collapseCohorts() concatenates cohort records, allowing for some number of days between one finishing and the next starting.

Usage

collapseCohorts(cohort, cohortId = NULL, gap = 0, name = tableName(cohort))
collapseCohorts(cohort, cohortId = NULL, gap = 0, name = tableName(cohort))

Arguments

`cohort`	A cohort table in a cdm reference.
`cohortId`	Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged.
`gap`	Number of days between two subsequent cohort entries to be merged in a single cohort record.
`name`	Name of the new cohort table created in the cdm object.

Value

A cohort table

Create cohorts based on a concept set

Description

conceptCohort() creates a cohort table from patient records from the clinical tables in the OMOP CDM.

The following tables are currently supported for creating concept cohorts:

condition_occurrence
device_exposure
drug_exposure
measurement
observation
procedure_occurrence
visit_occurrence

Cohort duration is based on record start and end (e.g. condition_start_date and condition_end_date for records coming from the condition_occurrence tables). So that the resulting table satisfies the requirements of an OMOP CDM cohort table:

Overlapping records are collapsed into a single cohort entry.
If a record starts outside of an observation period it will be silently ignored.
If a record ends outside of an observation period it will be trimmed so as to end at the preceding observation period end date.

Usage

conceptCohort(
  cdm,
  conceptSet,
  name,
  exit = "event_end_date",
  useSourceFields = FALSE,
  subsetCohort = NULL,
  subsetCohortId = NULL
)
conceptCohort(
  cdm,
  conceptSet,
  name,
  exit = "event_end_date",
  useSourceFields = FALSE,
  subsetCohort = NULL,
  subsetCohortId = NULL
)

Arguments

`cdm`	A cdm reference.
`conceptSet`	A conceptSet, which can either be a codelist or a conceptSetExpression.
`name`	Name of the new cohort table created in the cdm object.
`exit`	How the cohort end date is defined. Can be either "event_end_date" or "event_start_date".
`useSourceFields`	If TRUE, the source concept_id fields will also be used when identifying relevant clinical records. If FALSE, only the standard concept_id fields will be used.
`subsetCohort`	A cohort table containing individuals for whom cohorts will be generated. Only individuals in this table will appear in the generated cohort.
`subsetCohortId`	Optional. Specifies cohort IDs from the `subsetCohort` table to include. If none are provided, all cohorts from the `subsetCohort` are included.

Value

A cohort table

Examples


library(CohortConstructor)

cdm <- mockCohortConstructor(conditionOccurrence = TRUE)

cohort <- conceptCohort(cdm = cdm, conceptSet = list(a = 1), name = "cohort")

cohort |> attrition()

library(CohortConstructor)

cdm <- mockCohortConstructor(conditionOccurrence = TRUE)

cohort <- conceptCohort(cdm = cdm, conceptSet = list(a = 1), name = "cohort")

cohort |> attrition()

Create cohorts based on patient demographics

Description

demographicsCohort() creates a cohort table based on patient characteristics. If and when an individual satisfies all the criteria they enter the cohort. When they stop satisfying any of the criteria their cohort entry ends.

Usage

demographicsCohort(
  cdm,
  name,
  ageRange = NULL,
  sex = NULL,
  minPriorObservation = NULL
)
demographicsCohort(
  cdm,
  name,
  ageRange = NULL,
  sex = NULL,
  minPriorObservation = NULL
)

Arguments

`cdm`	A cdm reference.
`name`	Name of the new cohort table created in the cdm object.
`ageRange`	A list of vectors specifying minimum and maximum age.
`sex`	Can be "Both", "Male" or "Female".
`minPriorObservation`	A minimum number of continuous prior observation days in the database.

Value

A cohort table

Examples


library(CohortConstructor)

cdm <- mockCohortConstructor()

cohort <-  cdm |>
    demographicsCohort(name = "cohort3", ageRange = c(18,40), sex = "Male")

attrition(cohort)

library(CohortConstructor)

cdm <- mockCohortConstructor()

cohort <-  cdm |>
    demographicsCohort(name = "cohort3", ageRange = c(18,40), sex = "Male")

attrition(cohort)

Update cohort start date to be the first date from of a set of column dates

Description

entryAtFirstDate() resets cohort start date based on a set of specified column dates. The first date that occurs is chosen.

Usage

entryAtFirstDate(
  cohort,
  dateColumns,
  cohortId = NULL,
  returnReason = TRUE,
  name = tableName(cohort)
)
entryAtFirstDate(
  cohort,
  dateColumns,
  cohortId = NULL,
  returnReason = TRUE,
  name = tableName(cohort)
)

Arguments

`cohort`	A cohort table in a cdm reference.
`dateColumns`	Character vector indicating date columns in the cohort table to consider.
`cohortId`	Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged.
`returnReason`	If TRUE it will return a column indicating which of the `dateColumns` was used.
`name`	Name of the new cohort table created in the cdm object.

Value

The cohort table.

Examples


library(CohortConstructor)
cdm <- mockCohortConstructor(tables = list(
"cohort" = dplyr::tibble(
  cohort_definition_id = 1,
  subject_id = c(1, 2, 3, 4),
  cohort_start_date = as.Date(c("2000-06-03", "2000-01-01", "2015-01-15", "2000-12-09")),
  cohort_end_date = as.Date(c("2001-09-01", "2001-01-12", "2015-02-15", "2002-12-09")),
  date_1 = as.Date(c("2001-08-01", "2001-01-01", "2015-01-15", "2002-12-09")),
  date_2 = as.Date(c("2001-08-01", NA, "2015-02-14", "2002-12-09"))
)
))
cdm$cohort |> entryAtLastDate(dateColumns = c("date_1", "date_2"))

library(CohortConstructor)
cdm <- mockCohortConstructor(tables = list(
"cohort" = dplyr::tibble(
  cohort_definition_id = 1,
  subject_id = c(1, 2, 3, 4),
  cohort_start_date = as.Date(c("2000-06-03", "2000-01-01", "2015-01-15", "2000-12-09")),
  cohort_end_date = as.Date(c("2001-09-01", "2001-01-12", "2015-02-15", "2002-12-09")),
  date_1 = as.Date(c("2001-08-01", "2001-01-01", "2015-01-15", "2002-12-09")),
  date_2 = as.Date(c("2001-08-01", NA, "2015-02-14", "2002-12-09"))
)
))
cdm$cohort |> entryAtLastDate(dateColumns = c("date_1", "date_2"))

Set cohort start date to the last of a set of column dates

Description

entryAtLastDate() resets cohort end date based on a set of specified column dates. The last date is chosen.

Usage

entryAtLastDate(
  cohort,
  dateColumns,
  cohortId = NULL,
  returnReason = TRUE,
  name = tableName(cohort)
)
entryAtLastDate(
  cohort,
  dateColumns,
  cohortId = NULL,
  returnReason = TRUE,
  name = tableName(cohort)
)

Arguments

`cohort`	A cohort table in a cdm reference.
`dateColumns`	Character vector indicating date columns in the cohort table to consider.
`cohortId`	Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged.
`returnReason`	If TRUE it will return a column indicating which of the `dateColumns` was used.
`name`	Name of the new cohort table created in the cdm object.

Value

The cohort table.

Examples


library(CohortConstructor)
cdm <- mockCohortConstructor(tables = list(
"cohort" = dplyr::tibble(
  cohort_definition_id = 1,
  subject_id = c(1, 2, 3, 4),
  cohort_start_date = as.Date(c("2000-06-03", "2000-01-01", "2015-01-15", "2000-12-09")),
  cohort_end_date = as.Date(c("2001-09-01", "2001-01-12", "2015-02-15", "2002-12-09")),
  date_1 = as.Date(c("2001-08-01", "2001-01-01", "2015-01-15", "2002-12-09")),
  date_2 = as.Date(c("2001-08-01", NA, "2015-02-14", "2002-12-09"))
)
))
cdm$cohort |> entryAtLastDate(dateColumns = c("date_1", "date_2"))

library(CohortConstructor)
cdm <- mockCohortConstructor(tables = list(
"cohort" = dplyr::tibble(
  cohort_definition_id = 1,
  subject_id = c(1, 2, 3, 4),
  cohort_start_date = as.Date(c("2000-06-03", "2000-01-01", "2015-01-15", "2000-12-09")),
  cohort_end_date = as.Date(c("2001-09-01", "2001-01-12", "2015-02-15", "2002-12-09")),
  date_1 = as.Date(c("2001-08-01", "2001-01-01", "2015-01-15", "2002-12-09")),
  date_2 = as.Date(c("2001-08-01", NA, "2015-02-14", "2002-12-09"))
)
))
cdm$cohort |> entryAtLastDate(dateColumns = c("date_1", "date_2"))

Set cohort end date to death date

Description

This functions changes cohort end date to subject's death date. In the case were this generates overlapping records in the cohort, those overlapping entries will be merged.

Usage

exitAtDeath(
  cohort,
  cohortId = NULL,
  requireDeath = FALSE,
  name = tableName(cohort)
)
exitAtDeath(
  cohort,
  cohortId = NULL,
  requireDeath = FALSE,
  name = tableName(cohort)
)

Arguments

`cohort`	A cohort table in a cdm reference.
`cohortId`	Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged.
`requireDeath`	If TRUE, subjects without a death record will be dropped, while if FALSE their end date will be left as is.
`name`	Name of the new cohort table created in the cdm object.

Value

The cohort table.

Examples


library(PatientProfiles)
library(CohortConstructor)
cdm <- mockPatientProfiles()
cdm$cohort1 |> exitAtDeath()

library(PatientProfiles)
library(CohortConstructor)
cdm <- mockPatientProfiles()
cdm$cohort1 |> exitAtDeath()

Set cohort end date to the first of a set of column dates

Description

exitAtFirstDate() resets cohort end date based on a set of specified column dates. The first date that occurs is chosen.

Usage

exitAtFirstDate(
  cohort,
  dateColumns,
  cohortId = NULL,
  returnReason = TRUE,
  name = tableName(cohort)
)
exitAtFirstDate(
  cohort,
  dateColumns,
  cohortId = NULL,
  returnReason = TRUE,
  name = tableName(cohort)
)

Arguments

`cohort`	A cohort table in a cdm reference.
`dateColumns`	Character vector indicating date columns in the cohort table to consider.
`cohortId`	Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged.
`returnReason`	If TRUE it will return a column indicating which of the `dateColumns` was used.
`name`	Name of the new cohort table created in the cdm object.

Value

The cohort table.

Examples


library(CohortConstructor)
cdm <- mockCohortConstructor(tables = list(
"cohort" = dplyr::tibble(
  cohort_definition_id = 1,
  subject_id = c(1, 2, 3, 4),
  cohort_start_date = as.Date(c("2000-06-03", "2000-01-01", "2015-01-15", "2000-12-09")),
  cohort_end_date = as.Date(c("2001-09-01", "2001-01-12", "2015-02-15", "2002-12-09")),
  date_1 = as.Date(c("2001-08-01", "2001-01-01", "2015-01-15", "2002-12-09")),
  date_2 = as.Date(c("2001-08-01", NA, "2015-04-15", "2002-12-09"))
)
))
cdm$cohort |> exitAtFirstDate(dateColumns = c("date_1", "date_2"))

library(CohortConstructor)
cdm <- mockCohortConstructor(tables = list(
"cohort" = dplyr::tibble(
  cohort_definition_id = 1,
  subject_id = c(1, 2, 3, 4),
  cohort_start_date = as.Date(c("2000-06-03", "2000-01-01", "2015-01-15", "2000-12-09")),
  cohort_end_date = as.Date(c("2001-09-01", "2001-01-12", "2015-02-15", "2002-12-09")),
  date_1 = as.Date(c("2001-08-01", "2001-01-01", "2015-01-15", "2002-12-09")),
  date_2 = as.Date(c("2001-08-01", NA, "2015-04-15", "2002-12-09"))
)
))
cdm$cohort |> exitAtFirstDate(dateColumns = c("date_1", "date_2"))

Set cohort end date to the last of a set of column dates

Description

exitAtLastDate() resets cohort end date based on a set of specified column dates. The last date that occurs is chosen.

Usage

exitAtLastDate(
  cohort,
  dateColumns,
  cohortId = NULL,
  returnReason = TRUE,
  name = tableName(cohort)
)
exitAtLastDate(
  cohort,
  dateColumns,
  cohortId = NULL,
  returnReason = TRUE,
  name = tableName(cohort)
)

Arguments

`cohort`	A cohort table in a cdm reference.
`dateColumns`	Character vector indicating date columns in the cohort table to consider.
`cohortId`	Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged.
`returnReason`	If TRUE it will return a column indicating which of the `dateColumns` was used.
`name`	Name of the new cohort table created in the cdm object.

Value

The cohort table.

Examples


library(CohortConstructor)
cdm <- mockCohortConstructor(tables = list(
"cohort" = dplyr::tibble(
  cohort_definition_id = 1,
  subject_id = c(1, 2, 3, 4),
  cohort_start_date = as.Date(c("2000-06-03", "2000-01-01", "2015-01-15", "2000-12-09")),
  cohort_end_date = as.Date(c("2001-09-01", "2001-01-12", "2015-02-15", "2002-12-09")),
  date_1 = as.Date(c("2001-08-01", "2001-01-01", "2015-01-15", "2002-12-09")),
  date_2 = as.Date(c("2001-08-01", NA, "2015-04-15", "2002-12-09"))
)
))
cdm$cohort |> exitAtLastDate(dateColumns = c("date_1", "date_2"))

library(CohortConstructor)
cdm <- mockCohortConstructor(tables = list(
"cohort" = dplyr::tibble(
  cohort_definition_id = 1,
  subject_id = c(1, 2, 3, 4),
  cohort_start_date = as.Date(c("2000-06-03", "2000-01-01", "2015-01-15", "2000-12-09")),
  cohort_end_date = as.Date(c("2001-09-01", "2001-01-12", "2015-02-15", "2002-12-09")),
  date_1 = as.Date(c("2001-08-01", "2001-01-01", "2015-01-15", "2002-12-09")),
  date_2 = as.Date(c("2001-08-01", NA, "2015-04-15", "2002-12-09"))
)
))
cdm$cohort |> exitAtLastDate(dateColumns = c("date_1", "date_2"))

Set cohort end date to end of observation

Description

exitAtObservationEnd() resets cohort end date based on a set of specified column dates. The last date that occurs is chosen.

This functions changes cohort end date to the end date of the observation period corresponding to the cohort entry. In the case were this generates overlapping records in the cohort, overlapping entries will be merged.

Usage

exitAtObservationEnd(
  cohort,
  cohortId = NULL,
  limitToCurrentPeriod = TRUE,
  name = tableName(cohort)
)
exitAtObservationEnd(
  cohort,
  cohortId = NULL,
  limitToCurrentPeriod = TRUE,
  name = tableName(cohort)
)

Arguments

`cohort`	A cohort table in a cdm reference.
`cohortId`	Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged.
`limitToCurrentPeriod`	If TRUE, limits the cohort to one entry per person, ending at the current observation period. If FALSE, subsequent observation periods will create new cohort entries.
`name`	Name of the new cohort table created in the cdm object.

Value

The cohort table.

Examples


library(CohortConstructor)

cdm <- mockCohortConstructor()
cdm$cohort1 |> exitAtObservationEnd()

library(CohortConstructor)

cdm <- mockCohortConstructor()
cdm$cohort1 |> exitAtObservationEnd()

Generate a combination cohort set between the intersection of different cohorts.

Description

intersectCohorts() combines different cohort entries, with those records that overlap combined and kept. Cohort entries are when an individual was in both of the cohorts.

Usage

intersectCohorts(
  cohort,
  cohortId = NULL,
  gap = 0,
  returnNonOverlappingCohorts = FALSE,
  keepOriginalCohorts = FALSE,
  name = tableName(cohort)
)
intersectCohorts(
  cohort,
  cohortId = NULL,
  gap = 0,
  returnNonOverlappingCohorts = FALSE,
  keepOriginalCohorts = FALSE,
  name = tableName(cohort)
)

Arguments

`cohort`	A cohort table in a cdm reference.
`cohortId`	Vector identifying which cohorts to include (cohort_definition_id or cohort_name). Cohorts not included will be removed from the cohort set.
`gap`	Number of days between two subsequent cohort entries to be merged in a single cohort record.
`returnNonOverlappingCohorts`	Whether the generated cohorts are mutually exclusive or not.
`keepOriginalCohorts`	If TRUE the original cohorts will be return together with the new ones. If FALSE only the new cohort will be returned.
`name`	Name of the new cohort table created in the cdm object.

Value

A cohort table.

Examples


library(CohortConstructor)

cdm <- mockCohortConstructor(nPerson = 100)

cdm$cohort3 <- intersectCohorts(
  cohort = cdm$cohort2,
  name = "cohort3",
)

settings(cdm$cohort3)


library(CohortConstructor)

cdm <- mockCohortConstructor(nPerson = 100)

cdm$cohort3 <- intersectCohorts(
  cohort = cdm$cohort2,
  name = "cohort3",
)

settings(cdm$cohort3)

Generate a new cohort matched cohort

Description

matchCohorts() generate a new cohort matched to individuals in an existing cohort. Individuals can be matched based on year of birth and sex.

Usage

matchCohorts(
  cohort,
  cohortId = NULL,
  matchSex = TRUE,
  matchYearOfBirth = TRUE,
  ratio = 1,
  keepOriginalCohorts = FALSE,
  name = tableName(cohort)
)
matchCohorts(
  cohort,
  cohortId = NULL,
  matchSex = TRUE,
  matchYearOfBirth = TRUE,
  ratio = 1,
  keepOriginalCohorts = FALSE,
  name = tableName(cohort)
)

Arguments

`cohort`	A cohort table in a cdm reference.
`cohortId`	Vector identifying which cohorts to include (cohort_definition_id or cohort_name). Cohorts not included will be removed from the cohort set.
`matchSex`	Whether to match in sex.
`matchYearOfBirth`	Whether to match in year of birth.
`ratio`	Number of allowed matches per individual in the target cohort.
`keepOriginalCohorts`	If TRUE the original cohorts will be return together with the new ones. If FALSE only the new cohort will be returned.
`name`	Name of the new cohort table created in the cdm object.

Value

A cohort table.

Examples


library(CohortConstructor)
library(dplyr)
cdm <- mockCohortConstructor(nPerson = 200)
cdm$new_matched_cohort <- cdm$cohort2 |>
  matchCohorts(
    name = "new_matched_cohort",
    cohortId = 2,
    matchSex = TRUE,
    matchYearOfBirth = TRUE,
    ratio = 1)
cdm$new_matched_cohort

library(CohortConstructor)
library(dplyr)
cdm <- mockCohortConstructor(nPerson = 200)
cdm$new_matched_cohort <- cdm$cohort2 |>
  matchCohorts(
    name = "new_matched_cohort",
    cohortId = 2,
    matchSex = TRUE,
    matchYearOfBirth = TRUE,
    ratio = 1)
cdm$new_matched_cohort

Create cohorts measurement based cohorts

Description

measurementCohort() creates cohorts based on patient records contained in the measurement table. This function extends the conceptCohort() as it allows for measurement values associated with the records to be specified.

If valueAsConcept and valueAsNumber are NULL then no requirements on of the values associated with measurement records and using measurementCohort() will lead to the same result as using conceptCohort() (so long as all concepts are from the measurement domain).
If one of valueAsConcept and valueAsNumber is not NULL then records will be required to have values that satisfy the requirement specified.
If both valueAsConcept and valueAsNumber are not NULL, records will be required to have values that fulfill either of the requirements

Usage

measurementCohort(
  cdm,
  conceptSet,
  name,
  valueAsConcept = NULL,
  valueAsNumber = NULL
)
measurementCohort(
  cdm,
  conceptSet,
  name,
  valueAsConcept = NULL,
  valueAsNumber = NULL
)

Arguments

`cdm`	A cdm reference.
`conceptSet`	A conceptSet, which can either be a codelist or a conceptSetExpression.
`name`	Name of the new cohort table created in the cdm object.
`valueAsConcept`	A vector of cohort IDs used to filter measurements. Only measurements with these values in the `value_as_concept_id` column of the measurement table will be included. If NULL all entries independently of their value as concept will be considered.
`valueAsNumber`	A named list indicating the range of values and the unit they correspond to, as follows: list("unit_concept_id" = c(rangeValue1, rangeValue2)). If NULL, all entries independently of their value as number will be included.

Value

A cohort table

Examples


library(CohortConstructor)
cdm <- mockCohortConstructor(con = NULL)
cdm$concept <- cdm$concept |>
  dplyr::union_all(
    dplyr::tibble(
      concept_id = c(4326744, 4298393, 45770407, 8876, 4124457),
      concept_name = c("Blood pressure", "Systemic blood pressure",
                       "Baseline blood pressure", "millimeter mercury column",
                       "Normal range"),
      domain_id = "Measurement",
      vocabulary_id = c("SNOMED", "SNOMED", "SNOMED", "UCUM", "SNOMED"),
      standard_concept = "S",
      concept_class_id = c("Observable Entity", "Observable Entity",
                           "Observable Entity", "Unit", "Qualifier Value"),
      concept_code = NA,
      valid_start_date = NA,
      valid_end_date = NA,
      invalid_reason = NA
    )
  )
cdm$measurement <- dplyr::tibble(
  measurement_id = 1:4,
  person_id = c(1, 1, 2, 3),
  measurement_concept_id = c(4326744, 4298393, 4298393, 45770407),
  measurement_date = as.Date(c("2000-07-01", "2000-12-11", "2002-09-08",
                                "2015-02-19")),
  measurement_type_concept_id = NA,
  value_as_number = c(100, 125, NA, NA),
  value_as_concept_id = c(0, 0, 0, 4124457),
  unit_concept_id = c(8876, 8876, 0, 0)
)
cdm <- CDMConnector::copyCdmTo(
  con = DBI::dbConnect(duckdb::duckdb()),
  cdm = cdm, schema = "main")

cdm$cohort <- measurementCohort(
  cdm = cdm,
  name = "cohort",
  conceptSet = list("normal_blood_pressure" = c(4326744, 4298393, 45770407)),
  valueAsConcept = c(4124457),
  valueAsNumber = list("8876" = c(70, 120))
)

cdm$cohort

library(CohortConstructor)
cdm <- mockCohortConstructor(con = NULL)
cdm$concept <- cdm$concept |>
  dplyr::union_all(
    dplyr::tibble(
      concept_id = c(4326744, 4298393, 45770407, 8876, 4124457),
      concept_name = c("Blood pressure", "Systemic blood pressure",
                       "Baseline blood pressure", "millimeter mercury column",
                       "Normal range"),
      domain_id = "Measurement",
      vocabulary_id = c("SNOMED", "SNOMED", "SNOMED", "UCUM", "SNOMED"),
      standard_concept = "S",
      concept_class_id = c("Observable Entity", "Observable Entity",
                           "Observable Entity", "Unit", "Qualifier Value"),
      concept_code = NA,
      valid_start_date = NA,
      valid_end_date = NA,
      invalid_reason = NA
    )
  )
cdm$measurement <- dplyr::tibble(
  measurement_id = 1:4,
  person_id = c(1, 1, 2, 3),
  measurement_concept_id = c(4326744, 4298393, 4298393, 45770407),
  measurement_date = as.Date(c("2000-07-01", "2000-12-11", "2002-09-08",
                                "2015-02-19")),
  measurement_type_concept_id = NA,
  value_as_number = c(100, 125, NA, NA),
  value_as_concept_id = c(0, 0, 0, 4124457),
  unit_concept_id = c(8876, 8876, 0, 0)
)
cdm <- CDMConnector::copyCdmTo(
  con = DBI::dbConnect(duckdb::duckdb()),
  cdm = cdm, schema = "main")

cdm$cohort <- measurementCohort(
  cdm = cdm,
  name = "cohort",
  conceptSet = list("normal_blood_pressure" = c(4326744, 4298393, 45770407)),
  valueAsConcept = c(4124457),
  valueAsNumber = list("8876" = c(70, 120))
)

cdm$cohort

Function to create a mock cdm reference for CohortConstructor

Description

mockCohortConstructor() creates an example dataset that can be used for demonstrating and testing the package

Usage

mockCohortConstructor(
  nPerson = 10,
  conceptTable = NULL,
  tables = NULL,
  conceptId = NULL,
  conceptIdClass = NULL,
  drugExposure = FALSE,
  conditionOccurrence = FALSE,
  measurement = FALSE,
  death = FALSE,
  otherTables = NULL,
  con = DBI::dbConnect(duckdb::duckdb()),
  writeSchema = "main",
  seed = 123
)
mockCohortConstructor(
  nPerson = 10,
  conceptTable = NULL,
  tables = NULL,
  conceptId = NULL,
  conceptIdClass = NULL,
  drugExposure = FALSE,
  conditionOccurrence = FALSE,
  measurement = FALSE,
  death = FALSE,
  otherTables = NULL,
  con = DBI::dbConnect(duckdb::duckdb()),
  writeSchema = "main",
  seed = 123
)

Arguments

`nPerson`	number of person in the cdm
`conceptTable`	user defined concept table
`tables`	list of tables to include in the cdm
`conceptId`	list of concept id
`conceptIdClass`	the domain class of the conceptId
`drugExposure`	T/F include drug exposure table in the cdm
`conditionOccurrence`	T/F include condition occurrence in the cdm
`measurement`	T/F include measurement in the cdm
`death`	T/F include death table in the cdm
`otherTables`	it takes a list of single tibble with names to include other tables in the cdm
`con`	A DBI connection to create the cdm mock object.
`writeSchema`	Name of an schema on the same connection with writing permissions.
`seed`	Seed passed to omock::mockCdmFromTable

Value

cdm object

Examples


library(CohortConstructor)

cdm <- mockCohortConstructor()

cdm

library(CohortConstructor)

cdm <- mockCohortConstructor()

cdm

Set cohort start or cohort end

Description

Set cohort start or cohort end

Usage

padCohortDate(
  cohort,
  days,
  cohortDate = "cohort_start_date",
  indexDate = "cohort_start_date",
  collapse = TRUE,
  padObservation = TRUE,
  cohortId = NULL,
  name = tableName(cohort)
)
padCohortDate(
  cohort,
  days,
  cohortDate = "cohort_start_date",
  indexDate = "cohort_start_date",
  collapse = TRUE,
  padObservation = TRUE,
  cohortId = NULL,
  name = tableName(cohort)
)

Arguments

`cohort`	A cohort table in a cdm reference.
`days`	Integer with the number of days to add or name of a column (that must be numeric) to add.
`cohortDate`	'cohort_start_date' or 'cohort_end_date'.
`indexDate`	Variable in cohort that contains the index date to add.
`collapse`	Whether to collapse the overlapping records (TRUE) or drop the records that have an ongoing prior record.
`padObservation`	Whether to pad observations if they are outside observation_period (TRUE) or drop the records if they are outside observation_period (FALSE)
`cohortId`	Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged.
`name`	Name of the new cohort table created in the cdm object.

Value

Cohort table

Examples


library(CohortConstructor)
cdm <- mockCohortConstructor()
cdm$cohort1 |>
  padCohortDate(
    cohortDate = "cohort_end_date",
    indexDate = "cohort_start_date",
    days = 10)

library(CohortConstructor)
cdm <- mockCohortConstructor()
cdm$cohort1 |>
  padCohortDate(
    cohortDate = "cohort_end_date",
    indexDate = "cohort_start_date",
    days = 10)

Add days to cohort end

Description

padCohortEnd() Adds (or subtracts) a certain number of days to the cohort end date. Note:

If the days added means that cohort end would be after observation period end date, then observation period end date will be used for cohort exit.
If the days added means that cohort exit would be after the next cohort start then these overlapping cohort entries will be collapsed.
If days subtracted means that cohort end would be before cohort start then the cohort entry will be dropped.

Usage

padCohortEnd(
  cohort,
  days,
  collapse = TRUE,
  padObservation = TRUE,
  cohortId = NULL,
  name = tableName(cohort)
)
padCohortEnd(
  cohort,
  days,
  collapse = TRUE,
  padObservation = TRUE,
  cohortId = NULL,
  name = tableName(cohort)
)

Arguments

`cohort`	A cohort table in a cdm reference.
`days`	Integer with the number of days to add or name of a column (that must be numeric) to add.
`collapse`	Whether to collapse the overlapping records (TRUE) or drop the records that have an ongoing prior record.
`padObservation`	Whether to pad observations if they are outside observation_period (TRUE) or drop the records if they are outside observation_period (FALSE)
`cohortId`	Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged.
`name`	Name of the new cohort table created in the cdm object.

Value

Cohort table

Examples


library(CohortConstructor)
cdm <- mockCohortConstructor()
# add 10 days to each cohort exit
cdm$cohort1 |>
  padCohortEnd(days = 10)

library(CohortConstructor)
cdm <- mockCohortConstructor()
# add 10 days to each cohort exit
cdm$cohort1 |>
  padCohortEnd(days = 10)

Add days to cohort start

Description

padCohortStart() Adds (or subtracts) a certain number of days to the cohort start date. Note:

If the days added means that cohort start would be after cohort end then the cohort entry will be dropped.
If subtracting day means that cohort start would be before observation period start then the cohort entry will be dropped.

Usage

padCohortStart(
  cohort,
  days,
  collapse = TRUE,
  padObservation = TRUE,
  cohortId = NULL,
  name = tableName(cohort)
)
padCohortStart(
  cohort,
  days,
  collapse = TRUE,
  padObservation = TRUE,
  cohortId = NULL,
  name = tableName(cohort)
)

Arguments

`cohort`	A cohort table in a cdm reference.
`days`	Integer with the number of days to add or name of a column (that must be numeric) to add.
`collapse`	Whether to collapse the overlapping records (TRUE) or drop the records that have an ongoing prior record.
`padObservation`	Whether to pad observations if they are outside observation_period (TRUE) or drop the records if they are outside observation_period (FALSE)
`cohortId`	Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged.
`name`	Name of the new cohort table created in the cdm object.

Value

Cohort table

Examples


library(CohortConstructor)
cdm <- mockCohortConstructor()
# add 10 days to each cohort entry
cdm$cohort1 |>
  padCohortStart(days = 10)

library(CohortConstructor)
cdm <- mockCohortConstructor()
# add 10 days to each cohort entry
cdm$cohort1 |>
  padCohortStart(days = 10)

Restrict cohort on age

Description

requireAge() filters cohort records, keeping only records where individuals satisfy the specified age criteria.

Usage

requireAge(
  cohort,
  ageRange,
  cohortId = NULL,
  indexDate = "cohort_start_date",
  name = tableName(cohort)
)
requireAge(
  cohort,
  ageRange,
  cohortId = NULL,
  indexDate = "cohort_start_date",
  name = tableName(cohort)
)

Arguments

`cohort`	A cohort table in a cdm reference.
`ageRange`	A list of vectors specifying minimum and maximum age.
`cohortId`	Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged.
`indexDate`	Variable in cohort that contains the date to compute the demographics characteristics on which to restrict on.
`name`	Name of the new cohort table created in the cdm object.

Value

The cohort table with only records for individuals satisfying the age requirement

Examples


library(CohortConstructor)
cdm <- mockCohortConstructor()
cdm$cohort1 |>
  requireAge(indexDate = "cohort_start_date",
             ageRange = list(c(18, 65)))

library(CohortConstructor)
cdm <- mockCohortConstructor()
cdm$cohort1 |>
  requireAge(indexDate = "cohort_start_date",
             ageRange = list(c(18, 65)))

Require cohort subjects are present (or absence) in another cohort

Description

requireCohortIntersect() filters a cohort table based on a requirement that an individual is seen (or not seen) in another cohort in some time window around an index date.

Usage

requireCohortIntersect(
  cohort,
  targetCohortTable,
  window,
  intersections = c(1, Inf),
  cohortId = NULL,
  targetCohortId = NULL,
  indexDate = "cohort_start_date",
  targetStartDate = "cohort_start_date",
  targetEndDate = "cohort_end_date",
  censorDate = NULL,
  name = tableName(cohort)
)
requireCohortIntersect(
  cohort,
  targetCohortTable,
  window,
  intersections = c(1, Inf),
  cohortId = NULL,
  targetCohortId = NULL,
  indexDate = "cohort_start_date",
  targetStartDate = "cohort_start_date",
  targetEndDate = "cohort_end_date",
  censorDate = NULL,
  name = tableName(cohort)
)

Arguments

`cohort`	A cohort table in a cdm reference.
`targetCohortTable`	Name of the cohort that we want to check for intersect.
`window`	A list of vectors specifying minimum and maximum days from `indexDate` to consider events over.
`intersections`	A range indicating number of intersections for criteria to be fulfilled. If a single number is passed, the number of intersections must match this.
`cohortId`	Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged.
`targetCohortId`	Vector of cohort definition ids to include.
`indexDate`	Name of the column in the cohort that contains the date to compute the intersection.
`targetStartDate`	Start date of reference in cohort table.
`targetEndDate`	End date of reference in cohort table. If NULL, incidence of target event in the window will be considered as intersection, otherwise prevalence of that event will be used as intersection (overlap between cohort and event).
`censorDate`	Whether to censor overlap events at a specific date or a column date of the cohort.
`name`	Name of the new cohort table created in the cdm object.

Value

Cohort table with only those isatisfying the criteria kept

Examples


library(CohortConstructor)
cdm <- mockCohortConstructor()
cdm$cohort1 |>
  requireCohortIntersect(targetCohortTable = "cohort2",
                             targetCohortId = 1,
                             indexDate = "cohort_start_date",
                             window = c(-Inf, 0))

library(CohortConstructor)
cdm <- mockCohortConstructor()
cdm$cohort1 |>
  requireCohortIntersect(targetCohortTable = "cohort2",
                             targetCohortId = 1,
                             indexDate = "cohort_start_date",
                             window = c(-Inf, 0))

Require cohort subjects to have (or not have) events of a concept list

Description

requireConceptIntersect() filters a cohort table based on a requirement that an individual is seen (or not seen) to have events related to a concept list in some time window around an index date.

Usage

requireConceptIntersect(
  cohort,
  conceptSet,
  window,
  intersections = c(1, Inf),
  cohortId = NULL,
  indexDate = "cohort_start_date",
  targetStartDate = "event_start_date",
  targetEndDate = "event_end_date",
  censorDate = NULL,
  name = tableName(cohort)
)
requireConceptIntersect(
  cohort,
  conceptSet,
  window,
  intersections = c(1, Inf),
  cohortId = NULL,
  indexDate = "cohort_start_date",
  targetStartDate = "event_start_date",
  targetEndDate = "event_end_date",
  censorDate = NULL,
  name = tableName(cohort)
)

Arguments

`cohort`	A cohort table in a cdm reference.
`conceptSet`	A conceptSet, which can either be a codelist or a conceptSetExpression.
`window`	A list of vectors specifying minimum and maximum days from `indexDate` to consider events over.
`intersections`	A range indicating number of intersections for criteria to be fulfilled. If a single number is passed, the number of intersections must match this.
`cohortId`	Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged.
`indexDate`	Name of the column in the cohort that contains the date to compute the intersection.
`targetStartDate`	Start date of reference in cohort table.
`targetEndDate`	End date of reference in cohort table. If NULL, incidence of target event in the window will be considered as intersection, otherwise prevalence of that event will be used as intersection (overlap between cohort and event).
`censorDate`	Whether to censor overlap events at a specific date or a column date of the cohort.
`name`	Name of the new cohort table created in the cdm object.

Value

Cohort table with only those with the events in the concept list kept (or those without the event if negate = TRUE)

Examples


library(CohortConstructor)
cdm <- mockCohortConstructor(conditionOccurrence = TRUE)
cdm$cohort2 <-  requireConceptIntersect(
  cohort = cdm$cohort1,
  conceptSet = list(a = 194152),
  window = c(-Inf, 0),
  name = "cohort2")
  
library(CohortConstructor)
cdm <- mockCohortConstructor(conditionOccurrence = TRUE)
cdm$cohort2 <-  requireConceptIntersect(
  cohort = cdm$cohort1,
  conceptSet = list(a = 194152),
  window = c(-Inf, 0),
  name = "cohort2")

Require cohort subjects have (or do not have) a death record

Description

requireDeathFlag() filters a cohort table based on a requirement that an individual is seen (or not seen) to have a death in some time window around an index date.

Usage

requireDeathFlag(
  cohort,
  window,
  cohortId = NULL,
  indexDate = "cohort_start_date",
  censorDate = NULL,
  negate = FALSE,
  name = tableName(cohort)
)
requireDeathFlag(
  cohort,
  window,
  cohortId = NULL,
  indexDate = "cohort_start_date",
  censorDate = NULL,
  negate = FALSE,
  name = tableName(cohort)
)

Arguments

`cohort`	A cohort table in a cdm reference.
`window`	A list of vectors specifying minimum and maximum days from `indexDate` to consider events over.
`cohortId`	Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged.
`indexDate`	Name of the column in the cohort that contains the date to use as time 0 for window days.
`censorDate`	Whether to censor overlap events at a specific date or a column date of the cohort.
`negate`	If set as TRUE, criteria will be applied as exclusion rather than inclusion (i.e. require absence in another cohort).
`name`	Name of the new cohort table created in the cdm object.

Value

Cohort table with only those with a death event kept (or without if negate = TRUE)

Examples


library(CDMConnector)
library(CohortConstructor)
cdm <- mockCohortConstructor(death = TRUE)
cdm$cohort1 <- cdm$cohort1 |> requireDeathFlag(window = list(c(0, Inf)))
attrition(cdm$cohort1)

library(CDMConnector)
library(CohortConstructor)
cdm <- mockCohortConstructor(death = TRUE)
cdm$cohort1 <- cdm$cohort1 |> requireDeathFlag(window = list(c(0, Inf)))
attrition(cdm$cohort1)

Restrict cohort on patient demographics

Description

requireDemographics() filters cohort records, keeping only records where individuals satisfy the specified demographic criteria.

Usage

requireDemographics(
  cohort,
  cohortId = NULL,
  indexDate = "cohort_start_date",
  ageRange = list(c(0, 150)),
  sex = c("Both"),
  minPriorObservation = 0,
  minFutureObservation = 0,
  requirementInteractions = TRUE,
  name = tableName(cohort)
)
requireDemographics(
  cohort,
  cohortId = NULL,
  indexDate = "cohort_start_date",
  ageRange = list(c(0, 150)),
  sex = c("Both"),
  minPriorObservation = 0,
  minFutureObservation = 0,
  requirementInteractions = TRUE,
  name = tableName(cohort)
)

Arguments

`cohort`	A cohort table in a cdm reference.
`cohortId`	Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged.
`indexDate`	Variable in cohort that contains the date to compute the demographics characteristics on which to restrict on.
`ageRange`	A list of vectors specifying minimum and maximum age.
`sex`	Can be "Both", "Male" or "Female".
`minPriorObservation`	A minimum number of continuous prior observation days in the database.
`minFutureObservation`	A minimum number of continuous future observation days in the database.
`requirementInteractions`	If TRUE, cohorts will be created for all combinations of ageGroup, sex, and daysPriorObservation. If FALSE, only the first value specified for the other factors will be used. Consequently, order of values matters when requirementInteractions is FALSE.
`name`	Name of the new cohort table created in the cdm object.

Value

The cohort table with only records for individuals satisfying the demographic requirements

Examples


library(CohortConstructor)
cdm <- mockCohortConstructor(nPerson = 100)
cdm$cohort1 |>
  requireDemographics(indexDate = "cohort_start_date",
                      ageRange = list(c(18, 65)),
                      sex = "Female",
                      minPriorObservation = 365)

library(CohortConstructor)
cdm <- mockCohortConstructor(nPerson = 100)
cdm$cohort1 |>
  requireDemographics(indexDate = "cohort_start_date",
                      ageRange = list(c(18, 65)),
                      sex = "Female",
                      minPriorObservation = 365)

Restrict cohort on future observation

Description

requireFutureObservation() filters cohort records, keeping only records where individuals satisfy the specified future observation criteria.

Usage

requireFutureObservation(
  cohort,
  minFutureObservation,
  cohortId = NULL,
  indexDate = "cohort_start_date",
  name = tableName(cohort)
)
requireFutureObservation(
  cohort,
  minFutureObservation,
  cohortId = NULL,
  indexDate = "cohort_start_date",
  name = tableName(cohort)
)

Arguments

`cohort`	A cohort table in a cdm reference.
`minFutureObservation`	A minimum number of continuous future observation days in the database.
`cohortId`	Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged.
`indexDate`	Variable in cohort that contains the date to compute the demographics characteristics on which to restrict on.
`name`	Name of the new cohort table created in the cdm object.

Value

The cohort table with only records for individuals satisfying the future observation requirement

Examples


library(CohortConstructor)
cdm <- mockCohortConstructor()
cdm$cohort1 |>
  requireFutureObservation(indexDate = "cohort_start_date",
                           minFutureObservation = 30)

library(CohortConstructor)
cdm <- mockCohortConstructor()
cdm$cohort1 |>
  requireFutureObservation(indexDate = "cohort_start_date",
                           minFutureObservation = 30)

Require that an index date is within a date range

Description

requireInDateRange() filters cohort records, keeping only those for which the index date is within the specified date range.

Usage

requireInDateRange(
  cohort,
  dateRange,
  cohortId = NULL,
  indexDate = "cohort_start_date",
  name = tableName(cohort)
)
requireInDateRange(
  cohort,
  dateRange,
  cohortId = NULL,
  indexDate = "cohort_start_date",
  name = tableName(cohort)
)

Arguments

`cohort`	A cohort table in a cdm reference.
`dateRange`	A date vector with the minimum and maximum dates between which the index date must have been observed.
`cohortId`	Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged.
`indexDate`	Name of the column in the cohort that contains the date of interest.
`name`	Name of the new cohort table created in the cdm object.

Value

The cohort table with any cohort entries outside of the date range dropped

Examples


library(CohortConstructor)

cdm <- mockCohortConstructor(nPerson = 100)
cdm$cohort1 |>
  requireInDateRange(indexDate = "cohort_start_date",
                     dateRange = as.Date(c("2010-01-01", "2019-01-01")))

library(CohortConstructor)

cdm <- mockCohortConstructor(nPerson = 100)
cdm$cohort1 |>
  requireInDateRange(indexDate = "cohort_start_date",
                     dateRange = as.Date(c("2010-01-01", "2019-01-01")))

Restrict cohort to specific entry

Description

requireIsFirstEntry() filters cohort records, keeping only the first cohort entry per person.

Usage

requireIsEntry(cohort, entryRange, cohortId = NULL, name = tableName(cohort))
requireIsEntry(cohort, entryRange, cohortId = NULL, name = tableName(cohort))

Arguments

`cohort`	A cohort table in a cdm reference.
`entryRange`	Range for entries to include.
`cohortId`	Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged.
`name`	Name of the new cohort table created in the cdm object.

Value

A cohort table in a cdm reference.

Examples


library(CohortConstructor)
cdm <- mockCohortConstructor()
cdm$cohort1 <- requireIsEntry(cdm$cohort1, c(1, Inf))


library(CohortConstructor)
cdm <- mockCohortConstructor()
cdm$cohort1 <- requireIsEntry(cdm$cohort1, c(1, Inf))

Restrict cohort to first entry

Description

requireIsFirstEntry() filters cohort records, keeping only the first cohort entry per person.

Usage

requireIsFirstEntry(cohort, cohortId = NULL, name = tableName(cohort))
requireIsFirstEntry(cohort, cohortId = NULL, name = tableName(cohort))

Arguments

`cohort`	A cohort table in a cdm reference.
`cohortId`	Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged.
`name`	Name of the new cohort with the restriction.

Value

A cohort table in a cdm reference.

Examples


library(CohortConstructor)
cdm <- mockCohortConstructor()
cdm$cohort1 <- requireIsFirstEntry(cdm$cohort1)


library(CohortConstructor)
cdm <- mockCohortConstructor()
cdm$cohort1 <- requireIsFirstEntry(cdm$cohort1)

Restrict cohort to last entry per person

Description

requireIsLastEntry() filters cohort records, keeping only the last cohort entry per person.

Usage

requireIsLastEntry(cohort, cohortId = NULL, name = tableName(cohort))
requireIsLastEntry(cohort, cohortId = NULL, name = tableName(cohort))

Arguments

`cohort`	A cohort table in a cdm reference.
`cohortId`	IDs of the cohorts to modify. If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged.
`name`	Name of the new cohort with the restriction.

Value

A cohort table in a cdm reference.

Examples


library(CohortConstructor)
cdm <- mockCohortConstructor()
cdm$cohort1 <- requireIsLastEntry(cdm$cohort1)


library(CohortConstructor)
cdm <- mockCohortConstructor()
cdm$cohort1 <- requireIsLastEntry(cdm$cohort1)

Filter cohorts to keep only records for those with a minimum amount of subjects

Description

requireMinCohortCount() filters an existing cohort table, keeping only records from cohorts with a minimum number of individuals

Usage

requireMinCohortCount(
  cohort,
  minCohortCount,
  cohortId = NULL,
  name = tableName(cohort)
)
requireMinCohortCount(
  cohort,
  minCohortCount,
  cohortId = NULL,
  name = tableName(cohort)
)

Arguments

`cohort`	A cohort table in a cdm reference.
`minCohortCount`	The minimum count of sbjects for a cohort to be included.
`cohortId`	Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged.
`name`	Name of the new cohort table created in the cdm object.

Value

Cohort table

Examples


library(CohortConstructor)

cdm <- mockCohortConstructor(nPerson = 100)

cdm$cohort1 |>
requireMinCohortCount(5)

library(CohortConstructor)

cdm <- mockCohortConstructor(nPerson = 100)

cdm$cohort1 |>
requireMinCohortCount(5)

Restrict cohort on prior observation

Description

requirePriorObservation() filters cohort records, keeping only records where individuals satisfy the specified prior observation criteria.

Usage

requirePriorObservation(
  cohort,
  minPriorObservation,
  cohortId = NULL,
  indexDate = "cohort_start_date",
  name = tableName(cohort)
)
requirePriorObservation(
  cohort,
  minPriorObservation,
  cohortId = NULL,
  indexDate = "cohort_start_date",
  name = tableName(cohort)
)

Arguments

`cohort`	A cohort table in a cdm reference.
`minPriorObservation`	A minimum number of continuous prior observation days in the database.
`cohortId`	Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged.
`indexDate`	Variable in cohort that contains the date to compute the demographics characteristics on which to restrict on.
`name`	Name of the new cohort table created in the cdm object.

Value

The cohort table with only records for individuals satisfying the prior observation requirement

Examples


library(CohortConstructor)
cdm <- mockCohortConstructor()
cdm$cohort1 |>
  requirePriorObservation(indexDate = "cohort_start_date",
                          minPriorObservation = 365)

library(CohortConstructor)
cdm <- mockCohortConstructor()
cdm$cohort1 |>
  requirePriorObservation(indexDate = "cohort_start_date",
                          minPriorObservation = 365)

Restrict cohort on sex

Description

requireSex() filters cohort records, keeping only records where individuals satisfy the specified sex criteria.

Usage

requireSex(cohort, sex, cohortId = NULL, name = tableName(cohort))
requireSex(cohort, sex, cohortId = NULL, name = tableName(cohort))

Arguments

`cohort`	A cohort table in a cdm reference.
`sex`	Can be "Both", "Male" or "Female".
`cohortId`	Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged.
`name`	Name of the new cohort table created in the cdm object.

Value

The cohort table with only records for individuals satisfying the sex requirement

Examples


library(CohortConstructor)
cdm <- mockCohortConstructor()
cdm$cohort1 |>
  requireSex(sex = "Female")

library(CohortConstructor)
cdm <- mockCohortConstructor()
cdm$cohort1 |>
  requireSex(sex = "Female")

Require cohort subjects are present in another clinical table

Description

requireTableIntersect() filters a cohort table based on a requirement that an individual is seen (or not seen) to have a record (or no records) in a clinical table in some time window around an index date.

Usage

requireTableIntersect(
  cohort,
  tableName,
  window,
  intersections = c(1, Inf),
  cohortId = NULL,
  indexDate = "cohort_start_date",
  targetStartDate = startDateColumn(tableName),
  targetEndDate = endDateColumn(tableName),
  censorDate = NULL,
  name = tableName(cohort)
)
requireTableIntersect(
  cohort,
  tableName,
  window,
  intersections = c(1, Inf),
  cohortId = NULL,
  indexDate = "cohort_start_date",
  targetStartDate = startDateColumn(tableName),
  targetEndDate = endDateColumn(tableName),
  censorDate = NULL,
  name = tableName(cohort)
)

Arguments

`cohort`	A cohort table in a cdm reference.
`tableName`	Name of the table to check for intersect.
`window`	A list of vectors specifying minimum and maximum days from `indexDate` to consider events over.
`intersections`	A range indicating number of intersections for criteria to be fulfilled. If a single number is passed, the number of intersections must match this.
`cohortId`	Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged.
`indexDate`	Name of the column in the cohort that contains the date to compute the intersection.
`targetStartDate`	Start date of reference in cohort table.
`targetEndDate`	End date of reference in cohort table. If NULL, incidence of target event in the window will be considered as intersection, otherwise prevalence of that event will be used as intersection (overlap between cohort and event).
`censorDate`	Whether to censor overlap events at a specific date or a column date of the cohort.
`name`	Name of the new cohort table created in the cdm object.

Value

Cohort table with only those in the other table kept (or those that are not in the table if negate = TRUE)

Examples


library(CohortConstructor)
cdm <- mockCohortConstructor(drugExposure = TRUE)
cdm$cohort1 |>
  requireTableIntersect(tableName = "drug_exposure",
                            indexDate = "cohort_start_date",
                            window = c(-Inf, 0))

library(CohortConstructor)
cdm <- mockCohortConstructor(drugExposure = TRUE)
cdm$cohort1 |>
  requireTableIntersect(tableName = "drug_exposure",
                            indexDate = "cohort_start_date",
                            window = c(-Inf, 0))

Sample a cohort table for a given number of individuals.

Description

sampleCohorts() samples an existing cohort table for a given number of people. All records of these individuals are preserved.

Usage

sampleCohorts(cohort, n, cohortId = NULL, name = tableName(cohort))
sampleCohorts(cohort, n, cohortId = NULL, name = tableName(cohort))

Arguments

`cohort`	A cohort table in a cdm reference.
`n`	Number of people to be sampled for each included cohort.
`cohortId`	Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged.
`name`	Name of the new cohort table created in the cdm object.

Value

Cohort table with the specified cohorts sampled.

Examples


library(CohortConstructor)

cdm <- mockCohortConstructor(nPerson = 100)

cdm$cohort2 |> sampleCohorts(cohortId = 1, n = 10)

library(CohortConstructor)

cdm <- mockCohortConstructor(nPerson = 100)

cdm$cohort2 |> sampleCohorts(cohortId = 1, n = 10)

Create a new cohort table from stratifying an existing one

Description

stratifyCohorts() creates new cohorts, splitting an existing cohort based on specified columns on which to stratify on.

Usage

stratifyCohorts(
  cohort,
  strata,
  cohortId = NULL,
  removeStrata = TRUE,
  name = tableName(cohort)
)
stratifyCohorts(
  cohort,
  strata,
  cohortId = NULL,
  removeStrata = TRUE,
  name = tableName(cohort)
)

Arguments

`cohort`	A cohort table in a cdm reference.
`strata`	A strata list that point to columns in cohort table.
`cohortId`	Vector identifying which cohorts to include (cohort_definition_id or cohort_name). Cohorts not included will be removed from the cohort set.
`removeStrata`	Whether to remove strata columns from final cohort table.
`name`	Name of the new cohort table created in the cdm object.

Value

Cohort table stratified.

Examples


library(CohortConstructor)
library(PatientProfiles)

cdm <- mockCohortConstructor()

cdm$my_cohort <- cdm$cohort1 |>
  addAge(ageGroup = list("child" = c(0, 17), "adult" = c(18, Inf))) |>
  addSex(name = "my_cohort") |>
  stratifyCohorts(
    strata = list("sex", c("sex", "age_group")), name = "my_cohort"
  )

cdm$my_cohort

settings(cdm$my_cohort)

attrition(cdm$my_cohort)

library(CohortConstructor)
library(PatientProfiles)

cdm <- mockCohortConstructor()

cdm$my_cohort <- cdm$cohort1 |>
  addAge(ageGroup = list("child" = c(0, 17), "adult" = c(18, Inf))) |>
  addSex(name = "my_cohort") |>
  stratifyCohorts(
    strata = list("sex", c("sex", "age_group")), name = "my_cohort"
  )

cdm$my_cohort

settings(cdm$my_cohort)

attrition(cdm$my_cohort)

Generate a cohort table keeping a subset of cohorts.

Description

subsetCohorts() filters an existing cohort table, keeping only the records from cohorts that are specified.

Usage

subsetCohorts(cohort, cohortId, name = tableName(cohort))
subsetCohorts(cohort, cohortId, name = tableName(cohort))

Arguments

`cohort`	A cohort table in a cdm reference.
`cohortId`	Vector identifying which cohorts to include (cohort_definition_id or cohort_name). Cohorts not included will be removed from the cohort set.
`name`	Name of the new cohort table created in the cdm object.

Value

Cohort table with only cohorts in cohortId.

Examples


library(CohortConstructor)

cdm <- mockCohortConstructor(nPerson = 100)

cdm$cohort1 |> subsetCohorts(cohortId = 1)

library(CohortConstructor)

cdm <- mockCohortConstructor(nPerson = 100)

cdm$cohort1 |> subsetCohorts(cohortId = 1)

Restrict cohort on patient demographics

Description

trimDemographics() resets the cohort start and end date based on the specified demographic criteria is satisfied.

Usage

trimDemographics(
  cohort,
  cohortId = NULL,
  ageRange = NULL,
  sex = NULL,
  minPriorObservation = NULL,
  minFutureObservation = NULL,
  name = tableName(cohort)
)
trimDemographics(
  cohort,
  cohortId = NULL,
  ageRange = NULL,
  sex = NULL,
  minPriorObservation = NULL,
  minFutureObservation = NULL,
  name = tableName(cohort)
)

Arguments

`cohort`	A cohort table in a cdm reference.
`cohortId`	Vector identifying which cohorts to modify (cohort_definition_id or cohort_name). If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged.
`ageRange`	A list of vectors specifying minimum and maximum age.
`sex`	Can be "Both", "Male" or "Female".
`minPriorObservation`	A minimum number of continuous prior observation days in the database.
`minFutureObservation`	A minimum number of continuous future observation days in the database.
`name`	Name of the new cohort table created in the cdm object.

Value

The cohort table with only records for individuals satisfying the demographic requirements

Examples


library(CohortConstructor)

cdm <- mockCohortConstructor(nPerson = 100)

cdm$cohort1 |> trimDemographics(ageRange = list(c(10, 30)))

library(CohortConstructor)

cdm <- mockCohortConstructor(nPerson = 100)

cdm$cohort1 |> trimDemographics(ageRange = list(c(10, 30)))

Trim cohort dates to be within a date range

Description

trimToDateRange() resets the cohort start and end date based on the specified date range.

Usage

trimToDateRange(
  cohort,
  dateRange,
  cohortId = NULL,
  startDate = "cohort_start_date",
  endDate = "cohort_end_date",
  name = tableName(cohort)
)
trimToDateRange(
  cohort,
  dateRange,
  cohortId = NULL,
  startDate = "cohort_start_date",
  endDate = "cohort_end_date",
  name = tableName(cohort)
)

Arguments

`cohort`	A cohort table in a cdm reference.
`dateRange`	A window of time during which the index date must have been observed.
`cohortId`	IDs of the cohorts to modify. If NULL, all cohorts will be used; otherwise, only the specified cohorts will be modified, and the rest will remain unchanged.
`startDate`	Variable with earliest date.
`endDate`	Variable with latest date.
`name`	Name of the new cohort with the restriction.

Value

The cohort table with record timings updated to only be within the date range. Any records with all time outside of the range will have been dropped.

Examples


library(CohortConstructor)
cdm <- mockCohortConstructor()
cdm$cohort1 |>
  trimToDateRange(startDate = "cohort_start_date",
                  endDate = "cohort_end_date",
                  dateRange = as.Date(c("2015-01-01",
                                        "2015-12-31")))

library(CohortConstructor)
cdm <- mockCohortConstructor()
cdm$cohort1 |>
  trimToDateRange(startDate = "cohort_start_date",
                  endDate = "cohort_end_date",
                  dateRange = as.Date(c("2015-01-01",
                                        "2015-12-31")))

Generate cohort from the union of different cohorts

Description

unionCohorts() combines different cohort entries, with those records that overlap combined and kept. Cohort entries are when an individual was in either of the cohorts.

Usage

unionCohorts(
  cohort,
  cohortId = NULL,
  gap = 0,
  cohortName = NULL,
  keepOriginalCohorts = FALSE,
  name = tableName(cohort)
)
unionCohorts(
  cohort,
  cohortId = NULL,
  gap = 0,
  cohortName = NULL,
  keepOriginalCohorts = FALSE,
  name = tableName(cohort)
)

Arguments

`cohort`	A cohort table in a cdm reference.
`cohortId`	Vector identifying which cohorts to include (cohort_definition_id or cohort_name). Cohorts not included will be removed from the cohort set.
`gap`	Number of days between two subsequent cohort entries to be merged in a single cohort record.
`cohortName`	Name of the returned cohort. If NULL, the cohort name will be created by collapsing the individual cohort names, separated by "_".
`keepOriginalCohorts`	If TRUE the original cohorts will be return together with the new ones. If FALSE only the new cohort will be returned.
`name`	Name of the new cohort table created in the cdm object.

Value

A cohort table.

Examples


library(CohortConstructor)

cdm <- mockCohortConstructor(nPerson = 100)

cdm$cohort2 <- cdm$cohort2 |> unionCohorts()
settings(cdm$cohort2)


library(CohortConstructor)

cdm <- mockCohortConstructor(nPerson = 100)

cdm$cohort2 <- cdm$cohort2 |> unionCohorts()
settings(cdm$cohort2)

Generate a new cohort table restricting cohort entries to certain years

Description

yearCohorts() splits a cohort into multiple cohorts, one for each year.

Usage

yearCohorts(cohort, years, cohortId = NULL, name = tableName(cohort))
yearCohorts(cohort, years, cohortId = NULL, name = tableName(cohort))

Arguments

`cohort`	A cohort table in a cdm reference.
`years`	Numeric vector of years to use to restrict observation to..
`cohortId`	Vector identifying which cohorts to include (cohort_definition_id or cohort_name). Cohorts not included will be removed from the cohort set.
`name`	Name of the new cohort table created in the cdm object.

Value

A cohort table.

Examples


library(CohortConstructor)

cdm <- mockCohortConstructor(nPerson = 100)

cdm$cohort1 <- cdm$cohort1 |> yearCohorts(years = 2000:2002)
settings(cdm$cohort1)

library(CohortConstructor)

cdm <- mockCohortConstructor(nPerson = 100)

cdm$cohort1 <- cdm$cohort1 |> yearCohorts(years = 2000:2002)
settings(cdm$cohort1)

Package 'CohortConstructor'

Help Index

Add an index to a cohort table

Description

Usage

Arguments

Value

Benchmarking results

Description

Usage

Format

Collapse cohort entries using a certain gap to concatenate records.

Description

Usage

Arguments

Value

Create cohorts based on a concept set

Description

Usage

Arguments

Value

Examples

Create cohorts based on patient demographics

Description

Usage

Arguments

Value

Examples

Update cohort start date to be the first date from of a set of column dates

Description

Usage

Arguments

Value

Examples

Set cohort start date to the last of a set of column dates

Description

Usage

Arguments

Value

Examples

Set cohort end date to death date

Description

Usage

Arguments

Value

Examples

Set cohort end date to the first of a set of column dates

Description

Usage

Arguments

Value

Examples

Set cohort end date to the last of a set of column dates

Description

Usage

Arguments

Value

Examples

Set cohort end date to end of observation

Description

Usage

Arguments

Value

Examples

Generate a combination cohort set between the intersection of different cohorts.

Description

Usage

Arguments

Value

Examples

Generate a new cohort matched cohort

Description

Usage

Arguments

Value

Examples

Create cohorts measurement based cohorts

Description

Usage

Arguments